After the upscaling of a smaller image for display on high-resolution devices, edges within the upscaled image are often blurry (or blurrier) compared to images that are at the correct resolution or a higher resolution. In order to create sharper edges, image processing routines can use sharper scaling filters or a peaking circuit subsequent to the scaler. However, both of these techniques result in edges that have ringing (e.g., a thin ghosting or outline along sharp edges). In order to create sharp edges without ringing, non-linear edge enhancement or Digital Transient Improvement (DTi) algorithms are typically used.
FIG. 1 illustrates an example of a DTi system 100 in which a signal is received by an input component 102 and then upscaled by way of a scaling component 104. The upscaled signal is then processed by an edge enhancement and peaking component 106. The resulting signal is then transmitted by an output component 108.
Traditional one-dimensional (1D) Digital Transient improvement (DTi) algorithms are generally designed to provide additional sharpness along edges without introducing overshoot (e.g., overcorrection) or ringing (e.g., halo effect). However, this is a non-linear process that, when applied to edges that are not orthogonal to the filter, generally causes the edges to be overly processed, resulting in a non-smooth image (e.g., having jaggedness effects referred to as “jaggies”) instead of a smooth image.
There are several techniques that have been applied to provide edge enhancement without overshoot. For example, one technique includes the performing of a peaking operation on the signal and subsequently eliminating the ringing by way of a median filter. Such a median filter is applied to the peaked signal, a delayed version of the original signal, and an advanced version of the original signal. An example of this technique is illustrated by FIGS. 2A-2C, which are described below.
FIG. 2A illustrates a first signal capture 200A in which there is an edge 202A, before application of any peaking or filtering to the corresponding signal. FIG. 2B illustrates a second signal capture 200B in which there is an edge 202B representing the edge 202A of FIG. 2A after peaking and delayed and advanced versions thereof. FIG. 2C illustrates a third signal capture 200C in which there is a media filter result 202C corresponding to the original edge 202A of FIG. 2A.
An additional technique is described in U.S. Pat. No. 7,590,302 (“the '302 patent), which describes an image edge enhancement system and method. The '302 patent is hereby incorporated by reference herein.
While the techniques noted above may be effective for horizontal and vertical edges, such processes tend to degrade image quality in situations where image edges are at an odd angle.
FIGS. 3A-3B illustrate an example of the impact of applying a 1D DTi algorithm to a proper anti-alias edge. Whereas an edge 300A (FIG. 3A) has a smooth appearance, a resulting edge 300B (FIG. 3B) represents the edge 300A of FIG. 3A no longer having a smooth appearance due to such applying.
Traditional methods of adjusting a given technique based on the angle of the edge are complex due to the inherent difficulty in determining the angle itself. Further, the filter becomes more complex when the angles are not 0, 45, 90, or 135 degrees. Also, simply applying two 1D DTi algorithms at 0 and 90 degrees is likely to further increase the amount of jaggedness, e.g., vis a vis simply applying one algorithm or the other.
Accordingly, there remains a need for improved DTi techniques.